Fibrillation Complexity as a Predictor of Successful Defibrillation

A major focus of implantable cardioverter defibrillator (ICD) research has been to reduce the defibrillation shock energy to prolong battery life and provide an enhanced quality of life for the patient. We investigated whether the degree of disorganization (complexity) of the electrogram is correlated with defibrillation shock outcome. The study data sets were recorded using the high voltage leads of an ICD during device implantation. A total 57 data segments from 19 patients were analyzed. Beat cycles were identified using a novel wavelet based method. Two algorithms were proposed and implemented to quantify the disorganization of the electrogram signals: approximate entropy and cross correlation. Entropy Index based on the ApEn method, was able to discriminate successful episodes from failure ones with a specificity of 93% and sensitivity of 100%. Similarity index based on cross correlation method, obtained a specificity of 72% and sensitivity of 66%. We conclude that the organization of a VF episode is related to the minimum energy required for successful defibrillation